Overview

Dataset statistics

Number of variables18
Number of observations6514792
Missing cells8402940
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory894.7 MiB
Average record size in memory144.0 B

Variable types

Numeric7
Categorical11

Alerts

start_time has a high cardinality: 5259 distinct values High cardinality
blueprint has a high cardinality: 433 distinct values High cardinality
login has a high cardinality: 1144 distinct values High cardinality
position_x is highly correlated with map_width and 1 other fieldsHigh correlation
position_y is highly correlated with map_width and 1 other fieldsHigh correlation
map_width is highly correlated with position_x and 2 other fieldsHigh correlation
map_height is highly correlated with position_x and 2 other fieldsHigh correlation
position_x is highly correlated with map_width and 1 other fieldsHigh correlation
position_y is highly correlated with map_width and 1 other fieldsHigh correlation
map_width is highly correlated with position_x and 2 other fieldsHigh correlation
map_height is highly correlated with position_x and 2 other fieldsHigh correlation
position_y is highly correlated with map_width and 1 other fieldsHigh correlation
map_width is highly correlated with position_y and 1 other fieldsHigh correlation
map_height is highly correlated with position_y and 1 other fieldsHigh correlation
map_name is highly correlated with map_height and 2 other fieldsHigh correlation
map_height is highly correlated with map_name and 2 other fieldsHigh correlation
map_width is highly correlated with map_name and 2 other fieldsHigh correlation
map_thumbnail is highly correlated with map_name and 2 other fieldsHigh correlation
id is highly correlated with map_name and 1 other fieldsHigh correlation
position_x is highly correlated with position_y and 4 other fieldsHigh correlation
position_y is highly correlated with position_x and 4 other fieldsHigh correlation
faf_player_id is highly correlated with ratingHigh correlation
rating is highly correlated with faf_player_id and 2 other fieldsHigh correlation
map_name is highly correlated with id and 6 other fieldsHigh correlation
map_thumbnail is highly correlated with id and 6 other fieldsHigh correlation
map_width is highly correlated with position_x and 4 other fieldsHigh correlation
map_height is highly correlated with position_x and 4 other fieldsHigh correlation
blueprint has 4803912 (73.7%) missing values Missing
position_x has 1799514 (27.6%) missing values Missing
position_y has 1799514 (27.6%) missing values Missing
units_number has 152039 (2.3%) zeros Zeros
rating has 66783 (1.0%) zeros Zeros

Reproduction

Analysis started2022-07-28 03:00:28.657234
Analysis finished2022-07-28 03:07:02.323290
Duration6 minutes and 33.67 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct5351
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16394999.87
Minimum16260677
Maximum16462795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.7 MiB
2022-07-27T23:07:02.372691image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum16260677
5-th percentile16334755
Q116363608
median16395266
Q316428679
95-th percentile16457339
Maximum16462795
Range202118
Interquartile range (IQR)65071

Descriptive statistics

Standard deviation40501.70209
Coefficient of variation (CV)0.002470369162
Kurtosis-0.2667856269
Mean16394999.87
Median Absolute Deviation (MAD)32747
Skewness-0.2877496599
Sum1.06810014 × 1014
Variance1640387872
MonotonicityNot monotonic
2022-07-27T23:07:02.435896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1637177310268
 
0.2%
163563619147
 
0.1%
163791438534
 
0.1%
164058067261
 
0.1%
163928877087
 
0.1%
163343866889
 
0.1%
163331206862
 
0.1%
164566716624
 
0.1%
164341996514
 
0.1%
163913276381
 
0.1%
Other values (5341)6439225
98.8%
ValueCountFrequency (%)
16260677537
 
< 0.1%
16260678764
< 0.1%
162607121
 
< 0.1%
162607451054
< 0.1%
162607531803
< 0.1%
16260762792
< 0.1%
162607631021
< 0.1%
16260764752
< 0.1%
16260765953
< 0.1%
16260785370
 
< 0.1%
ValueCountFrequency (%)
164627952433
< 0.1%
164627812447
< 0.1%
164627691907
< 0.1%
164627301820
< 0.1%
164626982624
< 0.1%
164626803117
< 0.1%
16462666779
 
< 0.1%
164626482638
< 0.1%
16462632689
 
< 0.1%
16462609591
 
< 0.1%

start_time
Categorical

HIGH CARDINALITY

Distinct5259
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
2022-02-15 19:26:00 UTC
 
10268
2022-02-13 13:59:40 UTC
 
9147
2022-02-16 21:34:59 UTC
 
8534
2022-02-18 19:53:00 UTC
 
7523
2022-02-20 14:37:24 UTC
 
7261
Other values (5254)
6472059 

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters149840216
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)< 0.1%

Sample

1st row2022-02-15 00:36:27 UTC
2nd row2022-02-10 14:29:08 UTC
3rd row2022-02-23 15:58:04 UTC
4th row2022-02-18 19:25:59 UTC
5th row2022-02-23 19:48:59 UTC

Common Values

ValueCountFrequency (%)
2022-02-15 19:26:00 UTC10268
 
0.2%
2022-02-13 13:59:40 UTC9147
 
0.1%
2022-02-16 21:34:59 UTC8534
 
0.1%
2022-02-18 19:53:00 UTC7523
 
0.1%
2022-02-20 14:37:24 UTC7261
 
0.1%
2022-02-18 23:26:03 UTC7087
 
0.1%
2022-02-10 18:11:10 UTC6889
 
0.1%
2022-02-10 14:50:15 UTC6862
 
0.1%
2022-02-27 22:15:54 UTC6624
 
0.1%
2022-02-24 19:19:03 UTC6514
 
0.1%
Other values (5249)6438083
98.8%

Length

2022-07-27T23:07:02.495312image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
utc6514792
33.3%
2022-02-20476576
 
2.4%
2022-02-13401135
 
2.1%
2022-02-19396604
 
2.0%
2022-02-12388190
 
2.0%
2022-02-18377533
 
1.9%
2022-02-11366941
 
1.9%
2022-02-16346320
 
1.8%
2022-02-28329650
 
1.7%
2022-02-26329300
 
1.7%
Other values (4936)9617335
49.2%

Most occurring characters

ValueCountFrequency (%)
234847822
23.3%
021126463
14.1%
-13029584
 
8.7%
13029584
 
8.7%
:13029584
 
8.7%
112250027
 
8.2%
U6514792
 
4.3%
T6514792
 
4.3%
C6514792
 
4.3%
54807308
 
3.2%
Other values (6)18175468
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number91207088
60.9%
Uppercase Letter19544376
 
13.0%
Dash Punctuation13029584
 
8.7%
Space Separator13029584
 
8.7%
Other Punctuation13029584
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
234847822
38.2%
021126463
23.2%
112250027
 
13.4%
54807308
 
5.3%
34430209
 
4.9%
43638488
 
4.0%
82657186
 
2.9%
92496784
 
2.7%
72491705
 
2.7%
62461096
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
U6514792
33.3%
T6514792
33.3%
C6514792
33.3%
Dash Punctuation
ValueCountFrequency (%)
-13029584
100.0%
Space Separator
ValueCountFrequency (%)
13029584
100.0%
Other Punctuation
ValueCountFrequency (%)
:13029584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common130295840
87.0%
Latin19544376
 
13.0%

Most frequent character per script

Common
ValueCountFrequency (%)
234847822
26.7%
021126463
16.2%
-13029584
 
10.0%
13029584
 
10.0%
:13029584
 
10.0%
112250027
 
9.4%
54807308
 
3.7%
34430209
 
3.4%
43638488
 
2.8%
82657186
 
2.0%
Other values (3)7449585
 
5.7%
Latin
ValueCountFrequency (%)
U6514792
33.3%
T6514792
33.3%
C6514792
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII149840216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234847822
23.3%
021126463
14.1%
-13029584
 
8.7%
13029584
 
8.7%
:13029584
 
8.7%
112250027
 
8.2%
U6514792
 
4.3%
T6514792
 
4.3%
C6514792
 
4.3%
54807308
 
3.2%
Other values (6)18175468
12.1%

offset_ms
Real number (ℝ≥0)

Distinct56659
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean764053.742
Minimum0
Maximum19002400
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size49.7 MiB
2022-07-27T23:07:02.549073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70900
Q1295500
median574000
Q3997800
95-th percentile2126000
Maximum19002400
Range19002400
Interquartile range (IQR)702300

Descriptive statistics

Standard deviation723648.6516
Coefficient of variation (CV)0.947117476
Kurtosis33.89277023
Mean764053.742
Median Absolute Deviation (MAD)324900
Skewness3.417321711
Sum4.977651206 × 1012
Variance5.23667371 × 1011
MonotonicityNot monotonic
2022-07-27T23:07:02.607392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
433400710
 
< 0.1%
372700702
 
< 0.1%
75000691
 
< 0.1%
88800689
 
< 0.1%
346400688
 
< 0.1%
294500686
 
< 0.1%
88900685
 
< 0.1%
72800684
 
< 0.1%
336600683
 
< 0.1%
269400683
 
< 0.1%
Other values (56649)6507891
99.9%
ValueCountFrequency (%)
02
 
< 0.1%
18001
 
< 0.1%
19002
 
< 0.1%
200070
< 0.1%
21006
 
< 0.1%
22009
 
< 0.1%
230014
 
< 0.1%
240013
 
< 0.1%
250019
 
< 0.1%
260031
< 0.1%
ValueCountFrequency (%)
190024001
< 0.1%
189927001
< 0.1%
189910001
< 0.1%
189679001
< 0.1%
188895001
< 0.1%
188847001
< 0.1%
188672001
< 0.1%
188670001
< 0.1%
187624001
< 0.1%
187593001
< 0.1%

player
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
1
3311433 
0
3203359 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6514792
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

Length

2022-07-27T23:07:02.661664image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-27T23:07:02.709547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

Most occurring characters

ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6514792
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

Most occurring scripts

ValueCountFrequency (%)
Common6514792
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII6514792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13311433
50.8%
03203359
49.2%

type
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
issue
6311302 
factory_issue
 
203490

Length

Max length13
Median length5
Mean length5.249880579
Min length5

Characters and Unicode

Total characters34201880
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowissue
2nd rowissue
3rd rowissue
4th rowissue
5th rowissue

Common Values

ValueCountFrequency (%)
issue6311302
96.9%
factory_issue203490
 
3.1%

Length

2022-07-27T23:07:02.752811image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-27T23:07:02.803480image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
issue6311302
96.9%
factory_issue203490
 
3.1%

Most occurring characters

ValueCountFrequency (%)
s13029584
38.1%
i6514792
19.0%
u6514792
19.0%
e6514792
19.0%
f203490
 
0.6%
a203490
 
0.6%
c203490
 
0.6%
t203490
 
0.6%
o203490
 
0.6%
r203490
 
0.6%
Other values (2)406980
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter33998390
99.4%
Connector Punctuation203490
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s13029584
38.3%
i6514792
19.2%
u6514792
19.2%
e6514792
19.2%
f203490
 
0.6%
a203490
 
0.6%
c203490
 
0.6%
t203490
 
0.6%
o203490
 
0.6%
r203490
 
0.6%
Connector Punctuation
ValueCountFrequency (%)
_203490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin33998390
99.4%
Common203490
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s13029584
38.3%
i6514792
19.2%
u6514792
19.2%
e6514792
19.2%
f203490
 
0.6%
a203490
 
0.6%
c203490
 
0.6%
t203490
 
0.6%
o203490
 
0.6%
r203490
 
0.6%
Common
ValueCountFrequency (%)
_203490
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII34201880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s13029584
38.1%
i6514792
19.0%
u6514792
19.0%
e6514792
19.0%
f203490
 
0.6%
a203490
 
0.6%
c203490
 
0.6%
t203490
 
0.6%
o203490
 
0.6%
r203490
 
0.6%
Other values (2)406980
 
1.2%

units_number
Real number (ℝ≥0)

ZEROS

Distinct419
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.480246184
Minimum0
Maximum808
Zeros152039
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size49.7 MiB
2022-07-27T23:07:02.850012image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q35
95-th percentile30
Maximum808
Range808
Interquartile range (IQR)4

Descriptive statistics

Standard deviation14.46352855
Coefficient of variation (CV)2.231941217
Kurtosis101.2997295
Mean6.480246184
Median Absolute Deviation (MAD)0
Skewness6.977743756
Sum42217456
Variance209.1936582
MonotonicityNot monotonic
2022-07-27T23:07:03.109201image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13620529
55.6%
2443820
 
6.8%
3292261
 
4.5%
4226588
 
3.5%
5183199
 
2.8%
0152039
 
2.3%
6150437
 
2.3%
7119305
 
1.8%
8105060
 
1.6%
992683
 
1.4%
Other values (409)1128871
 
17.3%
ValueCountFrequency (%)
0152039
 
2.3%
13620529
55.6%
2443820
 
6.8%
3292261
 
4.5%
4226588
 
3.5%
5183199
 
2.8%
6150437
 
2.3%
7119305
 
1.8%
8105060
 
1.6%
992683
 
1.4%
ValueCountFrequency (%)
8081
 
< 0.1%
7842
< 0.1%
7591
 
< 0.1%
7531
 
< 0.1%
7031
 
< 0.1%
6952
< 0.1%
6811
 
< 0.1%
6703
< 0.1%
6503
< 0.1%
6021
 
< 0.1%

blueprint
Categorical

HIGH CARDINALITY
MISSING

Distinct433
Distinct (%)< 0.1%
Missing4803912
Missing (%)73.7%
Memory size49.7 MiB
ueb1103
 
123516
urb1103
 
120152
xsb1103
 
62653
url0107
 
60512
uel0201
 
55706
Other values (428)
1288341 

Length

Max length22
Median length7
Mean length7.004265641
Min length7

Characters and Unicode

Total characters11983458
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowurb1103
2nd rowueb1103
3rd rowueb1103
4th rowurb1103
5th rowueb0101

Common Values

ValueCountFrequency (%)
ueb1103123516
 
1.9%
urb1103120152
 
1.8%
xsb110362653
 
1.0%
url010760512
 
0.9%
uel020155706
 
0.9%
uel010545196
 
0.7%
url010545008
 
0.7%
ueb010142204
 
0.6%
urb010140545
 
0.6%
uab110339087
 
0.6%
Other values (423)1076301
 
16.5%
(Missing)4803912
73.7%

Length

2022-07-27T23:07:03.171956image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ueb1103123516
 
7.2%
urb1103120152
 
7.0%
xsb110362653
 
3.7%
url010760512
 
3.5%
uel020155706
 
3.3%
uel010545196
 
2.6%
url010545008
 
2.6%
ueb010142204
 
2.5%
urb010140545
 
2.4%
uab110339087
 
2.3%
Other values (423)1076301
62.9%

Most occurring characters

ValueCountFrequency (%)
02593830
21.6%
12416890
20.2%
u1362522
11.4%
b1016869
 
8.5%
2707520
 
5.9%
e639332
 
5.3%
3620547
 
5.2%
r592247
 
4.9%
l542828
 
4.5%
s318017
 
2.7%
Other values (23)1172856
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6841447
57.1%
Lowercase Letter5140549
42.9%
Connector Punctuation1462
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u1362522
26.5%
b1016869
19.8%
e639332
12.4%
r592247
11.5%
l542828
 
10.6%
s318017
 
6.2%
x316030
 
6.1%
a314062
 
6.1%
z16843
 
0.3%
d15555
 
0.3%
Other values (12)6244
 
0.1%
Decimal Number
ValueCountFrequency (%)
02593830
37.9%
12416890
35.3%
2707520
 
10.3%
3620547
 
9.1%
5210818
 
3.1%
4132218
 
1.9%
767669
 
1.0%
641346
 
0.6%
825337
 
0.4%
925272
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_1462
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6842909
57.1%
Latin5140549
42.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
u1362522
26.5%
b1016869
19.8%
e639332
12.4%
r592247
11.5%
l542828
 
10.6%
s318017
 
6.2%
x316030
 
6.1%
a314062
 
6.1%
z16843
 
0.3%
d15555
 
0.3%
Other values (12)6244
 
0.1%
Common
ValueCountFrequency (%)
02593830
37.9%
12416890
35.3%
2707520
 
10.3%
3620547
 
9.1%
5210818
 
3.1%
4132218
 
1.9%
767669
 
1.0%
641346
 
0.6%
825337
 
0.4%
925272
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII11983458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02593830
21.6%
12416890
20.2%
u1362522
11.4%
b1016869
 
8.5%
2707520
 
5.9%
e639332
 
5.3%
3620547
 
5.2%
r592247
 
4.9%
l542828
 
4.5%
s318017
 
2.7%
Other values (23)1172856
9.8%

position_x
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3281922
Distinct (%)69.6%
Missing1799514
Missing (%)27.6%
Infinite0
Infinite (%)0.0%
Mean247.2727416
Minimum-0.9999847412
Maximum1023.454834
Zeros6
Zeros (%)< 0.1%
Negative216
Negative (%)< 0.1%
Memory size49.7 MiB
2022-07-27T23:07:03.244361image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-0.9999847412
5-th percentile31.07578087
Q1113.3611832
median206.1904907
Q3346.6536331
95-th percentile619.0763
Maximum1023.454834
Range1024.454819
Interquartile range (IQR)233.29245

Descriptive statistics

Standard deviation182.2267471
Coefficient of variation (CV)0.7369463609
Kurtosis1.474881294
Mean247.2727416
Median Absolute Deviation (MAD)110.4556847
Skewness1.205535866
Sum1165959719
Variance33206.58736
MonotonicityNot monotonic
2022-07-27T23:07:03.302984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.57536
 
0.1%
30.57335
 
0.1%
211.57228
 
0.1%
18.56844
 
0.1%
50.56083
 
0.1%
209.55533
 
0.1%
31.55326
 
0.1%
46.55307
 
0.1%
22.55255
 
0.1%
489.55244
 
0.1%
Other values (3281912)4653587
71.4%
(Missing)1799514
 
27.6%
ValueCountFrequency (%)
-0.99998474121
< 0.1%
-0.99911499021
< 0.1%
-0.99830627441
< 0.1%
-0.99700927731
< 0.1%
-0.9950103761
< 0.1%
-0.98966979981
< 0.1%
-0.98825073241
< 0.1%
-0.98710632321
< 0.1%
-0.98681640621
< 0.1%
-0.98387908941
< 0.1%
ValueCountFrequency (%)
1023.4548341
< 0.1%
1023.1087651
< 0.1%
1022.732911
< 0.1%
1022.6756591
< 0.1%
1022.5620121
< 0.1%
1022.3613281
< 0.1%
1022.2744141
< 0.1%
1021.7414551
< 0.1%
1021.691041
< 0.1%
1021.6611331
< 0.1%

position_y
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3228670
Distinct (%)68.5%
Missing1799514
Missing (%)27.6%
Infinite0
Infinite (%)0.0%
Mean252.9292453
Minimum-0.9962081909
Maximum1023.842896
Zeros6
Zeros (%)< 0.1%
Negative66
Negative (%)< 0.1%
Memory size49.7 MiB
2022-07-27T23:07:03.383561image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-0.9962081909
5-th percentile34.90284214
Q1122.7977924
median212.5
Q3340.1143799
95-th percentile664.7243378
Maximum1023.842896
Range1024.839104
Interquartile range (IQR)217.3165874

Descriptive statistics

Standard deviation183.4765731
Coefficient of variation (CV)0.7254067155
Kurtosis1.893313646
Mean252.9292453
Median Absolute Deviation (MAD)104.5398636
Skewness1.327383004
Sum1192631706
Variance33663.65287
MonotonicityNot monotonic
2022-07-27T23:07:03.442183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.58066
 
0.1%
120.57475
 
0.1%
130.56871
 
0.1%
27.56787
 
0.1%
35.56520
 
0.1%
30.56220
 
0.1%
47.55751
 
0.1%
188.55351
 
0.1%
235.55201
 
0.1%
221.55135
 
0.1%
Other values (3228660)4651901
71.4%
(Missing)1799514
 
27.6%
ValueCountFrequency (%)
-0.99620819091
< 0.1%
-0.93524169921
< 0.1%
-0.91679382321
< 0.1%
-0.89186096191
< 0.1%
-0.88438415531
< 0.1%
-0.88275909421
< 0.1%
-0.87897491461
< 0.1%
-0.86877441411
< 0.1%
-0.86591339111
< 0.1%
-0.8607864381
< 0.1%
ValueCountFrequency (%)
1023.8428961
< 0.1%
1023.675721
< 0.1%
1023.6069341
< 0.1%
1022.1053471
< 0.1%
1021.8243411
< 0.1%
1021.6693121
< 0.1%
1021.3898321
< 0.1%
1021.333741
< 0.1%
1021.2585451
< 0.1%
1021.0484621
< 0.1%

command_name
Categorical

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
Move
3379522 
BuildMobile
780535 
BuildFactory
689989 
Reclaim
450781 
Attack
400288 
Other values (26)
813677 

Length

Max length28
Median length4
Mean length6.535027826
Min length4

Characters and Unicode

Total characters42574347
Distinct characters37
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStop
2nd rowTransportReverseLoadUnits
3rd rowStop
4th rowTransportLoadUnits
5th rowCapture

Common Values

ValueCountFrequency (%)
Move3379522
51.9%
BuildMobile780535
 
12.0%
BuildFactory689989
 
10.6%
Reclaim450781
 
6.9%
Attack400288
 
6.1%
Guard248961
 
3.8%
AggressiveMove187533
 
2.9%
Patrol129959
 
2.0%
Upgrade84634
 
1.3%
Repair40850
 
0.6%
Other values (21)121740
 
1.9%

Length

2022-07-27T23:07:03.497526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
move3379522
51.9%
buildmobile780535
 
12.0%
buildfactory689989
 
10.6%
reclaim450781
 
6.9%
attack400288
 
6.1%
guard248961
 
3.8%
aggressivemove187533
 
2.9%
patrol129959
 
2.0%
upgrade84634
 
1.3%
repair40850
 
0.6%
Other values (21)121740
 
1.9%

Most occurring characters

ValueCountFrequency (%)
e5358594
12.6%
o5285470
12.4%
M4368772
10.3%
v3787669
 
8.9%
i2999563
 
7.0%
l2849076
 
6.7%
a2117079
 
5.0%
d1826868
 
4.3%
t1736121
 
4.1%
u1727569
 
4.1%
Other values (27)10517566
24.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter34317155
80.6%
Uppercase Letter8257192
 
19.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5358594
15.6%
o5285470
15.4%
v3787669
11.0%
i2999563
8.7%
l2849076
8.3%
a2117079
 
6.2%
d1826868
 
5.3%
t1736121
 
5.1%
u1727569
 
5.0%
c1589704
 
4.6%
Other values (11)5039442
14.7%
Uppercase Letter
ValueCountFrequency (%)
M4368772
52.9%
B1470524
 
17.8%
F712745
 
8.6%
A592775
 
7.2%
R492399
 
6.0%
G248961
 
3.0%
P129959
 
1.6%
U119025
 
1.4%
S60551
 
0.7%
T28175
 
0.3%
Other values (6)33306
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Latin42574347
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5358594
12.6%
o5285470
12.4%
M4368772
10.3%
v3787669
 
8.9%
i2999563
 
7.0%
l2849076
 
6.7%
a2117079
 
5.0%
d1826868
 
4.3%
t1736121
 
4.1%
u1727569
 
4.1%
Other values (27)10517566
24.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII42574347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e5358594
12.6%
o5285470
12.4%
M4368772
10.3%
v3787669
 
8.9%
i2999563
 
7.0%
l2849076
 
6.7%
a2117079
 
5.0%
d1826868
 
4.3%
t1736121
 
4.1%
u1727569
 
4.1%
Other values (27)10517566
24.7%

faf_player_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1130
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240504.9518
Minimum145
Maximum437311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.7 MiB
2022-07-27T23:07:03.551211image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum145
5-th percentile15289
Q1105808
median248189
Q3383675
95-th percentile432747
Maximum437311
Range437166
Interquartile range (IQR)277867

Descriptive statistics

Standard deviation147190.9575
Coefficient of variation (CV)0.6120080121
Kurtosis-1.464348236
Mean240504.9518
Median Absolute Deviation (MAD)138377
Skewness-0.1675221872
Sum1.566839736 × 1012
Variance2.166517796 × 1010
MonotonicityNot monotonic
2022-07-27T23:07:03.607143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64928126011
 
1.9%
119070115783
 
1.8%
264292980
 
1.4%
40374376173
 
1.2%
3363274668
 
1.1%
17738265115
 
1.0%
34239864206
 
1.0%
6284862835
 
1.0%
39591962674
 
1.0%
15125761796
 
0.9%
Other values (1120)5712551
87.7%
ValueCountFrequency (%)
14522627
0.3%
25928793
0.4%
4344838
 
0.1%
43518794
0.3%
6063096
 
< 0.1%
64813001
0.2%
899381
 
< 0.1%
129410512
 
0.2%
1297247
 
< 0.1%
14996587
 
0.1%
ValueCountFrequency (%)
437311244
 
< 0.1%
437302748
 
< 0.1%
4373011315
 
< 0.1%
43726320
 
< 0.1%
437218136
 
< 0.1%
4371773495
0.1%
437109426
 
< 0.1%
4370634356
0.1%
4370595
 
< 0.1%
437048207
 
< 0.1%

login
Categorical

HIGH CARDINALITY

Distinct1144
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
Morax
 
126011
Cast_Away
 
115783
nemir
 
92980
indicator2020
 
76173
silentNoob
 
74668
Other values (1139)
6029177 

Length

Max length16
Median length13
Mean length8.527673025
Min length2

Characters and Unicode

Total characters55556016
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowTheWreck
2nd rowsilentNoob
3rd rowYellowNoob
4th rowCast_Away
5th rowSwkoll

Common Values

ValueCountFrequency (%)
Morax126011
 
1.9%
Cast_Away115783
 
1.8%
nemir92980
 
1.4%
indicator202076173
 
1.2%
silentNoob74668
 
1.1%
C_Buck65115
 
1.0%
hegesso64206
 
1.0%
Chenbro10162835
 
1.0%
Shadowrear62674
 
1.0%
Solstice24561796
 
0.9%
Other values (1134)5712551
87.7%

Length

2022-07-27T23:07:03.662544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
morax126011
 
1.9%
cast_away115783
 
1.8%
nemir92980
 
1.4%
indicator202076173
 
1.2%
silentnoob74668
 
1.1%
c_buck65115
 
1.0%
hegesso64206
 
1.0%
chenbro10162835
 
1.0%
shadowrear62674
 
1.0%
solstice24561796
 
0.9%
Other values (1133)5712551
87.7%

Most occurring characters

ValueCountFrequency (%)
a5019627
 
9.0%
e4291499
 
7.7%
o3862434
 
7.0%
r3822416
 
6.9%
n2817746
 
5.1%
i2747953
 
4.9%
t2362360
 
4.3%
s2247427
 
4.0%
l1803406
 
3.2%
h1452863
 
2.6%
Other values (54)25128285
45.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter42154282
75.9%
Uppercase Letter9289601
 
16.7%
Decimal Number3010963
 
5.4%
Connector Punctuation875066
 
1.6%
Dash Punctuation226104
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5019627
11.9%
e4291499
 
10.2%
o3862434
 
9.2%
r3822416
 
9.1%
n2817746
 
6.7%
i2747953
 
6.5%
t2362360
 
5.6%
s2247427
 
5.3%
l1803406
 
4.3%
h1452863
 
3.4%
Other values (16)11726551
27.8%
Uppercase Letter
ValueCountFrequency (%)
S794395
 
8.6%
N662464
 
7.1%
A607051
 
6.5%
T580264
 
6.2%
C559206
 
6.0%
B500819
 
5.4%
R497703
 
5.4%
M479090
 
5.2%
L454635
 
4.9%
D445138
 
4.8%
Other values (16)3708836
39.9%
Decimal Number
ValueCountFrequency (%)
0608636
20.2%
1562229
18.7%
2495445
16.5%
4259906
8.6%
3231177
 
7.7%
6191763
 
6.4%
5188169
 
6.2%
7170160
 
5.7%
9160534
 
5.3%
8142944
 
4.7%
Connector Punctuation
ValueCountFrequency (%)
_875066
100.0%
Dash Punctuation
ValueCountFrequency (%)
-226104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin51443883
92.6%
Common4112133
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5019627
 
9.8%
e4291499
 
8.3%
o3862434
 
7.5%
r3822416
 
7.4%
n2817746
 
5.5%
i2747953
 
5.3%
t2362360
 
4.6%
s2247427
 
4.4%
l1803406
 
3.5%
h1452863
 
2.8%
Other values (42)21016152
40.9%
Common
ValueCountFrequency (%)
_875066
21.3%
0608636
14.8%
1562229
13.7%
2495445
12.0%
4259906
 
6.3%
3231177
 
5.6%
-226104
 
5.5%
6191763
 
4.7%
5188169
 
4.6%
7170160
 
4.1%
Other values (2)303478
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII55556016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5019627
 
9.0%
e4291499
 
7.7%
o3862434
 
7.0%
r3822416
 
6.9%
n2817746
 
5.1%
i2747953
 
4.9%
t2362360
 
4.3%
s2247427
 
4.0%
l1803406
 
3.2%
h1452863
 
2.6%
Other values (54)25128285
45.2%

rating
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct2181
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean823.9001541
Minimum-602
Maximum2283
Zeros66783
Zeros (%)1.0%
Negative261154
Negative (%)4.0%
Memory size49.7 MiB
2022-07-27T23:07:03.716949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-602
5-th percentile0
Q1453
median760
Q31210
95-th percentile1754
Maximum2283
Range2885
Interquartile range (IQR)757

Descriptive statistics

Standard deviation522.7184424
Coefficient of variation (CV)0.6344439187
Kurtosis-0.4357332748
Mean823.9001541
Median Absolute Deviation (MAD)352
Skewness0.292974887
Sum5367538133
Variance273234.57
MonotonicityNot monotonic
2022-07-27T23:07:03.772045image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
066783
 
1.0%
49314836
 
0.2%
58313957
 
0.2%
83513666
 
0.2%
80213327
 
0.2%
56013099
 
0.2%
43112752
 
0.2%
76012367
 
0.2%
43812152
 
0.2%
69111957
 
0.2%
Other values (2171)6329896
97.2%
ValueCountFrequency (%)
-602653
 
< 0.1%
-600173
 
< 0.1%
-596254
 
< 0.1%
-5861453
< 0.1%
-565356
 
< 0.1%
-5641924
< 0.1%
-54419
 
< 0.1%
-53584
 
< 0.1%
-534185
 
< 0.1%
-517396
 
< 0.1%
ValueCountFrequency (%)
2283901
< 0.1%
2277644
 
< 0.1%
2271902
< 0.1%
22301113
< 0.1%
2226928
< 0.1%
22232078
< 0.1%
2217495
 
< 0.1%
22161000
< 0.1%
2209559
 
< 0.1%
22071763
< 0.1%

faction
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
UEF
2282944 
Cybran
2254063 
Seraphim
1221570 
Aeon
756215 

Length

Max length8
Median length6
Mean length5.091586961
Min length3

Characters and Unicode

Total characters33170630
Distinct characters17
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUEF
2nd rowCybran
3rd rowUEF
4th rowCybran
5th rowUEF

Common Values

ValueCountFrequency (%)
UEF2282944
35.0%
Cybran2254063
34.6%
Seraphim1221570
18.8%
Aeon756215
 
11.6%

Length

2022-07-27T23:07:03.826140image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-27T23:07:03.876707image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
uef2282944
35.0%
cybran2254063
34.6%
seraphim1221570
18.8%
aeon756215
 
11.6%

Most occurring characters

ValueCountFrequency (%)
r3475633
10.5%
a3475633
10.5%
n3010278
 
9.1%
E2282944
 
6.9%
U2282944
 
6.9%
F2282944
 
6.9%
b2254063
 
6.8%
y2254063
 
6.8%
C2254063
 
6.8%
e1977785
 
6.0%
Other values (7)7620280
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter22089950
66.6%
Uppercase Letter11080680
33.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r3475633
15.7%
a3475633
15.7%
n3010278
13.6%
b2254063
10.2%
y2254063
10.2%
e1977785
9.0%
p1221570
 
5.5%
h1221570
 
5.5%
i1221570
 
5.5%
m1221570
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
E2282944
20.6%
U2282944
20.6%
F2282944
20.6%
C2254063
20.3%
S1221570
11.0%
A756215
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Latin33170630
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r3475633
10.5%
a3475633
10.5%
n3010278
 
9.1%
E2282944
 
6.9%
U2282944
 
6.9%
F2282944
 
6.9%
b2254063
 
6.8%
y2254063
 
6.8%
C2254063
 
6.8%
e1977785
 
6.0%
Other values (7)7620280
23.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII33170630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r3475633
10.5%
a3475633
10.5%
n3010278
 
9.1%
E2282944
 
6.9%
U2282944
 
6.9%
F2282944
 
6.9%
b2254063
 
6.8%
y2254063
 
6.8%
C2254063
 
6.8%
e1977785
 
6.0%
Other values (7)7620280
23.0%

map_name
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
Oracle
1011204 
Loki - FAF version
1007624 
Open Palms
954503 
Stickleback Ridge
740717 
Esgaroth's Ruins
706330 
Other values (19)
2094414 

Length

Max length35
Median length28
Mean length17.04001371
Min length5

Characters and Unicode

Total characters111012145
Distinct characters48
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNorfair
2nd rowDesert Planet II v2
3rd rowNorfair
4th rowDesert Planet II v2
5th rowForbidden Pass - FAF version

Common Values

ValueCountFrequency (%)
Oracle1011204
15.5%
Loki - FAF version1007624
15.5%
Open Palms954503
14.7%
Stickleback Ridge740717
11.4%
Esgaroth's Ruins706330
10.8%
Theta Passage - FAF version675199
10.4%
Seraphim Glaciers - FAF version627190
9.6%
Point of Reach v4245451
 
3.8%
TAG Craftious Maximus - FAF version178688
 
2.7%
Tamara Pass175544
 
2.7%
Other values (14)192342
 
3.0%

Length

2022-07-27T23:07:03.929283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2550329
13.1%
faf2550329
13.1%
version2550329
13.1%
oracle1011204
 
5.2%
loki1007624
 
5.2%
open954503
 
4.9%
palms954503
 
4.9%
stickleback740717
 
3.8%
ridge740717
 
3.8%
ruins706330
 
3.6%
Other values (37)5632072
29.0%

Most occurring characters

ValueCountFrequency (%)
12883865
 
11.6%
e9101242
 
8.2%
s8488667
 
7.6%
a8148552
 
7.3%
i7724485
 
7.0%
r6109191
 
5.5%
F5138047
 
4.6%
o5065233
 
4.6%
n4583776
 
4.1%
l3378155
 
3.0%
Other values (38)40390932
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter75341874
67.9%
Uppercase Letter19238258
 
17.3%
Space Separator12883865
 
11.6%
Dash Punctuation2550329
 
2.3%
Other Punctuation706330
 
0.6%
Decimal Number289992
 
0.3%
Connector Punctuation1497
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e9101242
12.1%
s8488667
11.3%
a8148552
10.8%
i7724485
10.3%
r6109191
 
8.1%
o5065233
 
6.7%
n4583776
 
6.1%
l3378155
 
4.5%
c3365279
 
4.5%
v2850288
 
3.8%
Other values (14)16527006
21.9%
Uppercase Letter
ValueCountFrequency (%)
F5138047
26.7%
A2751309
14.3%
P2156536
11.2%
O1968328
 
10.2%
R1700246
 
8.8%
S1397792
 
7.3%
T1037179
 
5.4%
L1010245
 
5.3%
G805878
 
4.2%
E720515
 
3.7%
Other values (8)552183
 
2.9%
Decimal Number
ValueCountFrequency (%)
4245451
84.6%
244541
 
15.4%
Space Separator
ValueCountFrequency (%)
12883865
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2550329
100.0%
Other Punctuation
ValueCountFrequency (%)
'706330
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1497
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin94580132
85.2%
Common16432013
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e9101242
 
9.6%
s8488667
 
9.0%
a8148552
 
8.6%
i7724485
 
8.2%
r6109191
 
6.5%
F5138047
 
5.4%
o5065233
 
5.4%
n4583776
 
4.8%
l3378155
 
3.6%
c3365279
 
3.6%
Other values (32)33477505
35.4%
Common
ValueCountFrequency (%)
12883865
78.4%
-2550329
 
15.5%
'706330
 
4.3%
4245451
 
1.5%
244541
 
0.3%
_1497
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII111012145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12883865
 
11.6%
e9101242
 
8.2%
s8488667
 
7.6%
a8148552
 
7.3%
i7724485
 
7.0%
r6109191
 
5.5%
F5138047
 
4.6%
o5065233
 
4.6%
n4583776
 
4.1%
l3378155
 
3.0%
Other values (38)40390932
36.4%

map_thumbnail
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
https://content.faforever.com/maps/previews/large/oracle.v0005.png
1011204 
https://content.faforever.com/maps/previews/large/loki_-_faf_version.v0003.png
1007624 
https://content.faforever.com/maps/previews/large/scmp_007.png
954503 
https://content.faforever.com/maps/previews/large/stickleback_ridge.v0003.png
740717 
https://content.faforever.com/maps/previews/large/esgaroths ruins.png
706330 
Other values (19)
2094414 

Length

Max length95
Median length88
Mean length74.80420373
Min length62

Characters and Unicode

Total characters487333828
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://content.faforever.com/maps/previews/large/norfair.v0005.png
2nd rowhttps://content.faforever.com/maps/previews/large/desert planet ii v2.png
3rd rowhttps://content.faforever.com/maps/previews/large/norfair.v0005.png
4th rowhttps://content.faforever.com/maps/previews/large/desert planet ii v2.png
5th rowhttps://content.faforever.com/maps/previews/large/forbidden_pass_-_faf_version.v0004.png

Common Values

ValueCountFrequency (%)
https://content.faforever.com/maps/previews/large/oracle.v0005.png1011204
15.5%
https://content.faforever.com/maps/previews/large/loki_-_faf_version.v0003.png1007624
15.5%
https://content.faforever.com/maps/previews/large/scmp_007.png954503
14.7%
https://content.faforever.com/maps/previews/large/stickleback_ridge.v0003.png740717
11.4%
https://content.faforever.com/maps/previews/large/esgaroths ruins.png706330
10.8%
https://content.faforever.com/maps/previews/large/theta_passage_-_faf_version.v0001.png675199
10.4%
https://content.faforever.com/maps/previews/large/seraphim_glaciers_-_faf_version.v0001.png627190
9.6%
https://content.faforever.com/maps/previews/large/point of reach v4.png245451
 
3.8%
https://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png178688
 
2.7%
https://content.faforever.com/maps/previews/large/tamara_pass.v0001.png175544
 
2.7%
Other values (14)192342
 
3.0%

Length

2022-07-27T23:07:03.985390image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://content.faforever.com/maps/previews/large/oracle.v0005.png1011204
12.5%
https://content.faforever.com/maps/previews/large/loki_-_faf_version.v0003.png1007624
12.4%
https://content.faforever.com/maps/previews/large/scmp_007.png954503
11.8%
https://content.faforever.com/maps/previews/large/stickleback_ridge.v0003.png740717
9.1%
https://content.faforever.com/maps/previews/large/esgaroths706330
8.7%
ruins.png706330
8.7%
https://content.faforever.com/maps/previews/large/theta_passage_-_faf_version.v0001.png675199
8.3%
https://content.faforever.com/maps/previews/large/seraphim_glaciers_-_faf_version.v0001.png627190
7.7%
https://content.faforever.com/maps/previews/large/point245451
 
3.0%
of245451
 
3.0%
Other values (23)1181468
14.6%

Most occurring characters

ValueCountFrequency (%)
e47941539
 
9.8%
/39088752
 
8.0%
r33854138
 
6.9%
t29776845
 
6.1%
a29467316
 
6.0%
s29408417
 
6.0%
p28842894
 
5.9%
o25608967
 
5.3%
.24082667
 
4.9%
n23188865
 
4.8%
Other values (28)176073428
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter380828233
78.1%
Other Punctuation69686211
 
14.3%
Decimal Number21383693
 
4.4%
Connector Punctuation11298687
 
2.3%
Dash Punctuation2550329
 
0.5%
Space Separator1586675
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e47941539
12.6%
r33854138
 
8.9%
t29776845
 
7.8%
a29467316
 
7.7%
s29408417
 
7.7%
p28842894
 
7.6%
o25608967
 
6.7%
n23188865
 
6.1%
v20419660
 
5.4%
f18650105
 
4.9%
Other values (14)93669487
24.6%
Decimal Number
ValueCountFrequency (%)
015549555
72.7%
31761812
 
8.2%
11500148
 
7.0%
51055354
 
4.9%
7954503
 
4.5%
4459761
 
2.2%
273168
 
0.3%
829392
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/39088752
56.1%
.24082667
34.6%
:6514792
 
9.3%
Connector Punctuation
ValueCountFrequency (%)
_11298687
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2550329
100.0%
Space Separator
ValueCountFrequency (%)
1586675
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin380828233
78.1%
Common106505595
 
21.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e47941539
12.6%
r33854138
 
8.9%
t29776845
 
7.8%
a29467316
 
7.7%
s29408417
 
7.7%
p28842894
 
7.6%
o25608967
 
6.7%
n23188865
 
6.1%
v20419660
 
5.4%
f18650105
 
4.9%
Other values (14)93669487
24.6%
Common
ValueCountFrequency (%)
/39088752
36.7%
.24082667
22.6%
015549555
 
14.6%
_11298687
 
10.6%
:6514792
 
6.1%
-2550329
 
2.4%
31761812
 
1.7%
1586675
 
1.5%
11500148
 
1.4%
51055354
 
1.0%
Other values (4)1516824
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII487333828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e47941539
 
9.8%
/39088752
 
8.0%
r33854138
 
6.9%
t29776845
 
6.1%
a29467316
 
6.0%
s29408417
 
6.0%
p28842894
 
5.9%
o25608967
 
5.3%
.24082667
 
4.9%
n23188865
 
4.8%
Other values (28)176073428
36.1%

map_width
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
512
3441258 
256
2156743 
1024
916791 

Length

Max length4
Median length3
Mean length3.140724524
Min length3

Characters and Unicode

Total characters20461167
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1024
2nd row512
3rd row1024
4th row512
5th row512

Common Values

ValueCountFrequency (%)
5123441258
52.8%
2562156743
33.1%
1024916791
 
14.1%

Length

2022-07-27T23:07:04.034870image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-27T23:07:04.082472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
5123441258
52.8%
2562156743
33.1%
1024916791
 
14.1%

Most occurring characters

ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20461167
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common20461167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII20461167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

map_height
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.7 MiB
512
3441258 
256
2156743 
1024
916791 

Length

Max length4
Median length3
Mean length3.140724524
Min length3

Characters and Unicode

Total characters20461167
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1024
2nd row512
3rd row1024
4th row512
5th row512

Common Values

ValueCountFrequency (%)
5123441258
52.8%
2562156743
33.1%
1024916791
 
14.1%

Length

2022-07-27T23:07:04.125019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-27T23:07:04.171543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
5123441258
52.8%
2562156743
33.1%
1024916791
 
14.1%

Most occurring characters

ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number20461167
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common20461167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII20461167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26514792
31.8%
55598001
27.4%
14358049
21.3%
62156743
 
10.5%
0916791
 
4.5%
4916791
 
4.5%

Interactions

2022-07-27T23:06:10.601846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:32.154076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:39.186004image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:45.495557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:51.281297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:56.936565image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:04.060021image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:11.590845image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:33.214397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:40.099837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:46.371194image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:52.098775image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:57.744003image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:05.044079image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:12.589468image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:34.298252image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:41.040455image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:47.188532image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:52.902993image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:58.547876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:06.007171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:13.416642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:35.277804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:41.853900image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:47.934308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:53.684934image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:00.643312image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:06.831469image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:14.221460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:36.138842image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:42.661350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:48.668988image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:54.491223image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:01.417426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:07.640583image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:15.212893image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:37.205080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:43.646469image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:49.583019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:55.301536image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:02.229013image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:08.609906image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:16.170846image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:38.213368image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:44.608799image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:50.456801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:05:56.117445image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:03.028519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-07-27T23:06:09.618031image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-07-27T23:07:04.215080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-07-27T23:07:04.296633image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-07-27T23:07:04.376317image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-07-27T23:07:04.453854image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-07-27T23:07:04.530443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-07-27T23:06:20.415375image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-07-27T23:06:32.474585image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-07-27T23:06:51.245360image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-07-27T23:06:56.119530image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idstart_timeoffset_msplayertypeunits_numberblueprintposition_xposition_ycommand_namefaf_player_idloginratingfactionmap_namemap_thumbnailmap_widthmap_height
0163672812022-02-15 00:36:27 UTC7908000issue15NaNNaNNaNStop44051TheWreck1885UEFNorfairhttps://content.faforever.com/maps/previews/large/norfair.v0005.png10241024
1163330362022-02-10 14:29:08 UTC11132000issue1NaNNaNNaNTransportReverseLoadUnits33632silentNoob1712CybranDesert Planet II v2https://content.faforever.com/maps/previews/large/desert planet ii v2.png512512
2164268292022-02-23 15:58:04 UTC1865001issue1NaNNaNNaNStop206383YellowNoob1987UEFNorfairhttps://content.faforever.com/maps/previews/large/norfair.v0005.png10241024
3163910982022-02-18 19:25:59 UTC12908000issue9NaNNaNNaNTransportLoadUnits119070Cast_Away1666CybranDesert Planet II v2https://content.faforever.com/maps/previews/large/desert planet ii v2.png512512
4164284622022-02-23 19:48:59 UTC4554000issue1NaNNaNNaNCapture25711Swkoll2149UEFForbidden Pass - FAF versionhttps://content.faforever.com/maps/previews/large/forbidden_pass_-_faf_version.v0004.png512512
5163414192022-02-11 18:59:14 UTC10702000issue4NaN303.411865111.591949FormMove119070Cast_Away1636CybranDesert Planet II v2https://content.faforever.com/maps/previews/large/desert planet ii v2.png512512
6164520802022-02-27 11:48:59 UTC311000issue1NaNNaNNaNStop206383YellowNoob1955UEFForbidden Pass - FAF versionhttps://content.faforever.com/maps/previews/large/forbidden_pass_-_faf_version.v0004.png512512
7163791432022-02-16 21:34:59 UTC22749001issue15NaNNaNNaNTransportLoadUnits64928Morax1811CybranDesert Planet II v2https://content.faforever.com/maps/previews/large/desert planet ii v2.png512512
8162617492022-02-01 05:38:13 UTC1891001issue6NaNNaNNaNTransportLoadUnits287686demonstreamer6661553CybranWhite Fire - FAF versionhttps://content.faforever.com/maps/previews/large/white_fire_-_faf_version.v0002.png512512
9164530362022-02-27 14:13:16 UTC7032000issue1NaN510.855286450.782532Ferry229724Novdino1545AeonNorfairhttps://content.faforever.com/maps/previews/large/norfair.v0005.png10241024

Last rows

idstart_timeoffset_msplayertypeunits_numberblueprintposition_xposition_ycommand_namefaf_player_idloginratingfactionmap_namemap_thumbnailmap_widthmap_height
6514782164591912022-02-28 11:57:50 UTC10070001issue8NaN403.683502249.417191AggressiveMove298933CheeseBerry1278SeraphimTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514783163800032022-02-17 00:37:57 UTC6376000issue5NaN188.160904330.224243AggressiveMove64928Morax1798CybranTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514784164267092022-02-23 15:31:00 UTC7712000issue25NaN242.952194161.408295AggressiveMove434782Kalkbrenner1258AeonTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514785163495092022-02-12 18:20:12 UTC1777001issue4NaN293.124359147.393021AggressiveMove219084Conorach1388CybranTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514786163715952022-02-15 19:02:03 UTC2597001issue1NaN208.845963323.309753AggressiveMove373105grimplex1907UEFTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514787164150082022-02-21 19:37:00 UTC4451001issue2NaN392.935974224.796936AggressiveMove64928Morax1801CybranTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514788163673602022-02-15 01:03:28 UTC3875000issue2NaN204.560776174.036285AggressiveMove275960RowanMorseYT1629SeraphimTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514789163794272022-02-16 22:25:56 UTC13530001issue1NaN378.457092104.579559AggressiveMove62848Chenbro1011274CybranTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514790163390252022-02-11 12:59:11 UTC1492000factory_issue1NaN122.546814180.407104AggressiveMove62848Chenbro1011254CybranTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512
6514791163600122022-02-13 21:00:26 UTC7977001factory_issue1NaN455.219452213.843216AggressiveMove131692o-o-o1087AeonTAG Craftious Maximus - FAF versionhttps://content.faforever.com/maps/previews/large/tag_craftious_maximus_-_faf_version.v0004.png512512